Embodiments described herein generally relate to the registration of images, and in particular to the registration of images derived from medical image data.
In the medical field, two-dimensional (2D) and three-dimensional (3D) image data sets are collected by a variety of techniques—referred to as modalities in the field—including conventional X-ray, computer-assisted tomography (CT), magnetic resonance (MR), ultrasound and positron-emission-tomography (PET). Examples of 2D images include not only conventional X-ray images, but also 2D images derived from 3D image data sets, i.e. volume data sets, such as a “slice” of a CT scan or a “slab” of volume data from a CT scan in a multi-planar reformatting (MPR) view. Time resolved 3D studies are also well known and are usually referred to as 4D studies, with time being the fourth “dimension”. For example, time-resolved perfusion in abdominal organs is measured using 4D dynamic contrast enhanced CT (DCE-CT). It is also known to co-present images of the same patient taken with different modalities, such as combining CT and PET scans into a single image. These combined representations are sometimes referred to as 5D studies.
A common task when analyzing medical image data is a desire to compare one image with another, for example, to compare a patient image from one time with a corresponding image of the patient from another time or other reference image. In order to compare first and second medical images it can be useful to spatially transform one of the images to attempt to align corresponding body parts from the two images. This process is known as image registration. Image registration may be performed with a view to displaying the registered image to a user for direct visual inspection or to assist automated processing techniques, such as automated image segmentation.
In some situations registration might be applied for relatively small images of a specific body part, for example to compare an image of a patient's heart with another heart image. In other cases, registration might be applied on a larger scale, for example for registering images of relatively large parts of a body, such as a thorax. Large-scale image registration may sometimes be referred to as “whole-body” registration. This term may be used generally for large-scale image registration, for example in the context of medical images containing several different anatomical features, and should not be interpreted as necessarily requiring an entire complete body image from head to toe. In some cases, two images which are to be compared may not have the same extent. For example, in some situations there may be a desire to register a relatively small study image against a larger reference image (for example, a whole-body atlas image)
Large-scale medical image registration, for example of whole-body images, can be more difficult to perform successfully than smaller-scale medical image registration. This can be due to the wide variations in the appearance and relative locations and orientations of anatomical features between different patients, and also differences in patient position/orientations when comparing images from the same patient.
Accordingly, there are a need to provide improved schemes for medical image registration, and in particular in the context of medical image registration involving relatively large-scale medical images.